Dynamics and determinants of Brazilian banking efficiency using stochastic frontier panel models
Main Article Content
Abstract
The study estimates banking efficiency both in general and segmented (Retail and Wholesale) as well as its temporal dynamics. The results of this study made it possible to identify relevant macroeconomic variables for efficiency, as well as to analyze efficiency performance in recessionary periods. The results indicate a heterogeneity of relevant variables for each bank, and therefore for each segmentation, as well as different efficiency reactions in periods of economic recession. These results allow the development of other research on this topic and are also pioneers for the Brazilian case, as far as the authors are aware.
Article Details
References
Aigner, D. J., Knox-Lovell, C. e Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models, The Rand Paper Series P-5649, The Rand Corporation. https://www.rand.org/content/dam/rand/pubs/papers/2008/P5649.pdf
Alnabulsi, K., Kozarević, E. e Hakimi, A. (2023). Non-performing loans and net interest margin in the MENA region: Linear and non-linear analyses, International Journal of Financial Studies, 11(2), 64. https://doi.org/10.3390/ijfs11020064
Andries, A. M. (2011). The determinants of bank efficiency and productivity growth in the central and eastern European banking systems, Eastern European Economics, 49(6), 38–59. http://www.jstor.org/stable/41408826
Bair, E., Hastie, T., Paul, D. e Tibshirani, R. (2006). Prediction by supervised principal components, Journal of the American Statistical Association, 101(473), 119–137. https://doi.org/10.1198/016214505000000628
Battese, G. e Coelli, T. (1992). Frontier production functions, technical efficiency and panel data: With application to paddy farmers in india, Journal of Productivity Analysis, 3(1/2), 153–169. http://www.jstor.org/stable/41770578
Berger, A., Hunter, W. e Timme, S. (1993). The efficiency of financial institutions: A review and preview of research past, present and future, Journal of Banking and Finance, 17(2-3), 221–249. https://doi.org/10.1016/0378-4266(93)90030-H
Berger, A. e Mester, L. (1997). Inside the black box: What explains differences in the efficiencies of financial institutions?, Journal of Banking and Finance, 21(7), 895–947. https://doi.org/10.1016/S0378-4266(97)00010-1
Cornwell, C., Schmidt, P. e Sickles, R. (1989). Production frontiers with cross-sectional and time-series variation in efficiency levels, Journal of Econometrics, 46(1-2), 185–200. https://doi.org/10.1016/0304-4076(90)90054-W
Demirgüç-Kunt, A. e Huizinga, H. (1999). Determinants of commercial bank interest margins and profitability: Some international evidence, The World Bank Economic Review, 13(2), 379–408. http://www.jstor.org/stable/3990103
Dietrich, A. e Wanzenried, G. (2014). The determinants of commercial banking profitability in low-, middle-, and high-income countries, The Quarterly Review of Economics and Finance, 54(3), 337–354. https://doi.org/10.1016/j.qref.2014.03.001
Greene, W. (2005). Fixed and random effects in stochastic frontier models, Journal of Productivity Analysis, 23(1), 7–32. http://www.jstor.org/stable/41770178
Jurado, K., Ludvigson, S. C. e Ng, S. (2015). Measuring uncertainty, American Economic Review, 105(3), 1177–1216. https://doi.org/10.1257/aer.20131193
Kumbhakar, S. C., Lien, G. e Hardaker, J. B. (2014). Technical efficiency in competing panel data models: A study of Norwegian grain farming, Journal of Productivity Analysis, 41(2), 321–337. http://www.jstor.org/stable/43550001
Kumbhakar, S. C., Wang, H. J. e Horncastle, A. P. (2015). A practitioner’s guide to stochastic frontier analysis using Stata, Cambridge University Press. https://doi.org/10.1017/CBO9781139342070
Meeusen, W. e van Den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error, International Economic Review, 18(2), 435–444. https://doi.org/10.2307/2525757
Murillo-Zamorano, L. R. (2004). Economic efficiency and frontier techniques, Journal of Economic Surveys, 18(1), 33–77. https://doi.org/10.1111/j.1467-6419.2004.00215.x
Santomero, A. M. (1984). Modeling the banking firm: A survey, Journal of Money, Credit and Banking, 16(4), 576–602. http://www.jstor.org/stable/1992092
Saona, P. (2016). Intra- and extra-bank determinants of Latin American banks’ profitability, International Review of Economics and Finance, 45, 197–214. https://doi.org/10.1016/j.iref.2016.06.004
Schmidt, P. e Sickles, R. C. (1984). Production frontiers and panel data, Journal of Business and Economic Statistics, 2(4), 367–374. http://www.jstor.org/stable/1391278
Shen, B., Perfilev, A. A., Bufetova, L. P. e Li, X. (2023). Bank profitability analysis in China: Stochastic frontier approach, Journal of Risk and Financial Management, 16(4), 243. https://doi.org/10.3390/jrfm16040243
Tsionas, E. G. (2002). Stochastic frontier models with random coefficients, Journal of Applied Econometrics, 17(2), 127–147. http://www.jstor.org/stable/4129247
